Growth and Labour Input in North America
Bibliographic record
Abstract
Output growth slowed in the US and Mexico in the first quarter of 2007, while the Canadian economy accelerated. The US and Mexico both suffered from weak export growth, with the housing market continuing to put strain on domestic demand growth in the US. In aggregate, North American growth slowed to just 0.3 per cent relative to the previous quarter. Inflation accelerated in both the US and Canada in the first half of 2007, prompting a rise in Canadian interest rates. Rising inflation stems partly from tight labour markets, which have put upward pressure on wages. Labour market pressures in Canada are likely to be offset by the impact of the 6 per cent rise in the country's effective exchange rate between the first and second quarters of 2007, whilst the renewed weakness of the dollar, which fell by 2 per cent in effective terms between the first and second quarters of 2007, is likely to exacerbate inflationary pressures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".